If customer retention is what keeps you awake at night, then you’ll want to hear what Sanjiv Patel has to say. As director of data science for Cisco, Sanjiv plays a leadership role in our company- and partner-wide digital transformation. Kelly Crothers, director of strategy, planning and thought leadership, recently sat down with Sanjiv to discuss how partners can use data science to improve customer health and success.
Kelly: First off, how does data science impact the customer journey at Cisco?
Sanjiv: As Cisco began building its customer success practice a few years ago, it became clear that we also needed to build a strong data science foundation for the initiative. Through data science, we can gain a deeper understanding of the customer’s journey and engage in more effective conversations throughout the customer lifecycle. In the past year, our data science efforts have accelerated and my role has been centered on expanding our machine learning and predictive and prescriptive analytics capabilities to deliver a more powerful digital experience to our customers. It’s been gratifying to see the impact. For example, data-driven digital touchpoints led to a 21% increase in subscription renewals in one year, fueling increased customer retention.
Kelly: Can you tell us about the data science models you’re using and how they add value to the customer journey?
Sanjiv: Our data science models look at our customers from a who, what, when, where and why perspective. The “who” models focus on reaching the right customer contacts. The “what” models focus on the messages we present to them to address their specific needs. We have a recommendation engine–similar to Amazon’s–that predicts what each customer is likely to purchase across Cisco’s entire portfolio in the next three months. We can use that information in different ways to execute a touchpoint at the appropriate time in the customer lifecycle. The “when” models allow us to target specific customers at specific times, based on their interaction history with us. The goal is to get the timing right – to engage with them when they’re most likely to see our messages and extract value from them. The “where” models determine which digital channels best suit each customer: we’ve scored each customer based on their preferences, such as email, web and social. Lastly, the “why” models address specific problems, such as predicting that the customer is facing setbacks with a product, or that they are not likely to renew with us. These models prompt us to take corrective action.
Kelly: I’ve heard you mention Cisco’s “digital brain.” Tell us more about that.
Sanjiv: When you combine the “who, what, when, where and why” models and aggregate the incoming data in one central place, the result is what I call Cisco’s “digital brain.” That brain maps out our engagements with each customer based on their journey with us. Taking our “brainpower” a step further, we use machine learning to help our team identify all the ways they can make the journey for the customer more personalized. The idea is to eliminate mass messaging and even segmented messaging. We want to treat each customer engagement as a “market of one.”
Kelly: How can partners get started with data science?
Sanjiv: It’s easy to get intimidated by all the different metrics. My best advice is to start simple: this video interview offers a few of my ideas for how and where to begin. To solve the issue of how to reach your best or biggest customers using digital touchpoints, gathering the data you need is typically very easy. That information is front and center in your business. The challenge becomes more complex with your broader base of customers, especially when you consider the multitude of lifecycle touchpoints required to nurture success across each product or service the customer is using. That’s where our partner-focused offerings like Lifecycle Advantage come in. They are essentially hardwired to our “who, what, where, when and why” models, and provide partners with the ability to deliver timely, scalable and automated touchpoints—along with an immersive, personalized digital experience—to the customer.
Kelly: What is one message you’d like to leave with our partners when it comes to data science?
Sanjiv: Don’t wait. When it comes to serving your customers, it’s a race against time to deliver value. Through data insights, you can gain a deeper understanding of the customer’s journey in real time, which means you’re not only able to serve them better, but you can also establish a more profitable and rewarding future for your business.
How can partners get started with data science? Watch the video now.